# tf.GraphKeys
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| [ View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/framework/ops.py#L5988-L6130) |
Standard names to use for graph collections.
#### View aliases
**Compat aliases for migration**
See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.
[`tf.compat.v1.GraphKeys`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/GraphKeys)
The standard library uses various well-known names to collect and
retrieve values associated with a graph. For example, the
`tf.Optimizer` subclasses default to optimizing the variables
collected under [`tf.GraphKeys.TRAINABLE_VARIABLES`](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/GraphKeys#TRAINABLE_VARIABLES) if none is
specified, but it is also possible to pass an explicit list of
variables.
The following standard keys are defined:
- `GLOBAL_VARIABLES`: the default collection of `Variable` objects, shared across distributed environment (model variables are subset of these). See [`tf.compat.v1.global_variables`](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/global_variables) for more details. Commonly, all `TRAINABLE_VARIABLES` variables will be in `MODEL_VARIABLES`, and all `MODEL_VARIABLES` variables will be in `GLOBAL_VARIABLES`.
- `LOCAL_VARIABLES`: the subset of `Variable` objects that are local to each machine. Usually used for temporarily variables, like counters. Note: use [`tf.contrib.framework.local_variable`](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/framework/local_variable) to add to this collection.
- `MODEL_VARIABLES`: the subset of `Variable` objects that are used in the model for inference (feed forward). Note: use [`tf.contrib.framework.model_variable`](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/framework/model_variable) to add to this collection.
- `TRAINABLE_VARIABLES`: the subset of `Variable` objects that will be trained by an optimizer. See [`tf.compat.v1.trainable_variables`](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/trainable_variables) for more details.
- `SUMMARIES`: the summary `Tensor` objects that have been created in the graph. See [`tf.compat.v1.summary.merge_all`](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/summary/merge_all) for more details.
- `QUEUE_RUNNERS`: the `QueueRunner` objects that are used to produce input for a computation. See [`tf.compat.v1.train.start_queue_runners`](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/train/queue_runner/start_queue_runners) for more details.
- `MOVING_AVERAGE_VARIABLES`: the subset of `Variable` objects that will also keep moving averages. See [`tf.compat.v1.moving_average_variables`](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/moving_average_variables) for more details.
- `REGULARIZATION_LOSSES`: regularization losses collected during graph construction.
The following standard keys are *defined* , but their collections are **not**
automatically populated as many of the others are:
- `WEIGHTS`
- `BIASES`
- `ACTIVATIONS`
## Class Variables
- `ACTIVATIONS = 'activations'`
- `ASSET_FILEPATHS = 'asset_filepaths'`
- `BIASES = 'biases'`
- `CONCATENATED_VARIABLES = 'concatenated_variables'`
- `COND_CONTEXT = 'cond_context'`
- `EVAL_STEP = 'eval_step'`
- `GLOBAL_STEP = 'global_step'`
- `GLOBAL_VARIABLES = 'variables'`
- `INIT_OP = 'init_op'`
- `LOCAL_INIT_OP = 'local_init_op'`
- `LOCAL_RESOURCES = 'local_resources'`
- `LOCAL_VARIABLES = 'local_variables'`
- `LOSSES = 'losses'`
- `METRIC_VARIABLES = 'metric_variables'`
- `MODEL_VARIABLES = 'model_variables'`
- `MOVING_AVERAGE_VARIABLES = 'moving_average_variables'`
- `QUEUE_RUNNERS = 'queue_runners'`
- `READY_FOR_LOCAL_INIT_OP = 'ready_for_local_init_op'`
- `READY_OP = 'ready_op'`
- `REGULARIZATION_LOSSES = 'regularization_losses'`
- `RESOURCES = 'resources'`
- `SAVEABLE_OBJECTS = 'saveable_objects'`
- `SAVERS = 'savers'`
- `SUMMARIES = 'summaries'`
- `SUMMARY_OP = 'summary_op'`
- `TABLE_INITIALIZERS = 'table_initializer'`
- `TRAINABLE_RESOURCE_VARIABLES = 'trainable_resource_variables'`
- `TRAINABLE_VARIABLES = 'trainable_variables'`
- `TRAIN_OP = 'train_op'`
- `UPDATE_OPS = 'update_ops'`
- `VARIABLES = 'variables'`
- `WEIGHTS = 'weights'`
- `WHILE_CONTEXT = 'while_context'`